Book Image

Mastering Elasticsearch 5.x - Third Edition

By : Bharvi Dixit
Book Image

Mastering Elasticsearch 5.x - Third Edition

By: Bharvi Dixit

Overview of this book

Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. Elasticsearch leverages the capabilities of Apache Lucene, and provides a new level of control over how you can index and search even huge sets of data. This book will give you a brief recap of the basics and also introduce you to the new features of Elasticsearch 5. We will guide you through the intermediate and advanced functionalities of Elasticsearch, such as querying, indexing, searching, and modifying data. We’ll also explore advanced concepts, including aggregation, index control, sharding, replication, and clustering. We’ll show you the modules of monitoring and administration available in Elasticsearch, and will also cover backup and recovery. You will get an understanding of how you can scale your Elasticsearch cluster to contextualize it and improve its performance. We’ll also show you how you can create your own analysis plugin in Elasticsearch. By the end of the book, you will have all the knowledge necessary to master Elasticsearch and put it to efficient use.
Table of Contents (20 chapters)
Mastering Elasticsearch 5.x - Third Edition
Credits
About the Author
Acknowledgements
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Preface

Welcome to the world of Elasticsearch and Mastering Elasticsearch 5.x, Third Edition. While reading the book, you'll be taken through different topics—all connected to Elasticsearch. Please remember though that this book is not meant for beginners, and we really treat the book as a follow-up to Mastering Elasticsearch 5.x, Second Edition, which was based on Elasticsearch version 1.4.x. There is a lot of new content in the book since Elasticsearch has gone through many changes between versions 1.x and 5.x.

Throughout the book, we will discuss different topics related to Elasticsearch and Lucene. We start with an introduction to the world of Lucene and Elasticsearch to introduce you to the world of queries provided by Elasticsearch, where we discuss different topics related to queries, such as filtering and which query to choose in a particular situation. Of course, querying is not everything, and because of that, the book you are holding in your hands provides information on newly introduced aggregations and features that will help you give meaning to the data you have indexed in Elasticsearch indices and provide a better search experience for your users.

We have also decided to cover the approaches of data modeling and handling relational data in Elasticsearch along with taking you through the scripting module of Elasticsearch and show some examples of using the latest default scripting language, Painless.

Even though, for most users, querying and data analysis are the most interesting parts of Elasticsearch, they are not all that we need to discuss. Because of this, the book tries to bring you additional information when it comes to index architecture, such as choosing the right number of shards and replicas, adjusting the shard allocation behavior, and so on. We will also get into places where Elasticsearch meets Lucene, and we will discuss topics such as different scoring algorithms, choosing the right store mechanism, what the differences between them are, and why choosing the proper one matters.

Last but not least, we touch on the administration part of Elasticsearch by discussing discovery and recovery modules and the human-friendly cat API, which allows us to very quickly get relevant administrative information in a form that most humans should be able to read without parsing JSON responses. We also talk about ingest nodes, which allow you to preprocess data within Elasticsearch before indexing takes place and use tribe nodes, giving the ability to create federated searches across many nodes.

Because of the title of the book, we couldn't omit performance-related topics, and we decided to dedicate a whole chapter to it.

Just as with the second edition of the book, we decided to include a chapter dedicated to development of Elasticsearch plugins, showing you how to set up the Apache Maven project and develop two types of plugins—custom REST action and custom analysis.

At the end, we have included one chapter discussing the components of the complete Elastic Stack, and you should get a great overview of how to start with tools such as Logstash, Kibana, and Beats after reading the chapter.

If you think that you are interested in these topics after reading about them, we think this is a book for you, and hopefully, you will like the book after reading the last words of the summary in Chapter 12, Introducing Elastic Stack 5.0.

What this book covers

Chapter 1, Revisiting Elasticsearch and the Changes, guides you through how Apache Lucene works and will introduce you to Elasticsearch 5.x, describing the basic concepts and showing you the important changes in Elasticsearch from version 1.x to 5.x.

Chapter 2, The Improved Query DSL, describes the new default scoring algorithm, BM25, and how it would be better than the previous TF-IDF algorithm. In addition to that, it explains various Elasticsearch features, such as query rewriting, query templates, changes in query modules, and various queries to choose from in a given scenario.

Chapter 3, Beyond Full Text Search, describes queries about rescoring, multimatching control, and function score queries. In addition to that, this chapter covers the scripting module of Elasticsearch.

Chapter 4, Data Modeling and Analytics, discusses different approaches of data modeling in Elasticsearch and also covers how to handle relationships among documents using parent-child and nested data types, along with focusing on practical considerations. It further discusses the aggregation module of Elasticsearch for the purpose of data analytics.

Chapter 5, Improving the User Search Experience, focuses on topics for improving the user search experience using suggesters, which allows you to correct user-query spelling mistakes and build efficient autocomplete mechanisms. In addition to that, it covers how to improve query relevance and how to use synonyms to search.

Chapter 6, The Index Distribution Architecture, covers techniques for choosing the right amount of shards and replicas, how routing works, how shard allocation works, and how to alter its behavior. In addition to that, we discuss what query execution preference is and how it allows us to choose where the queries are going to be executed.

Chapter 7, Low-Level Index Control, describes how to alter Apache Lucene scoring and how to choose an alternative scoring algorithm. It also covers NRT searching and indexing and transaction log usage and allows you to understand segment merging and tune it for your use case along with the details about removed merge policies inside Elasticsearch 5.x. At the end of the chapter, you will also find information about IO throttling and Elasticsearch caching.

Chapter 8, Elasticsearch Administration, focuses on concepts related to administering Elasticsearch. It describes what the discovery, gateway, and recovery modules are, how to configure them, and why you should bother. We also describe what the cat API is and how to back up and restore your data to different cloud services (such as Amazon AWS and Microsoft Azure).

Chapter 9, Data Transformation and Federated Search, covers the latest feature of Elasticsearch 5, that is ingest node, which allows us to preprocess data into the Elasticsearch cluster itself before indexing. It further tells us about how federated search works with different clusters using tribe nodes.

Chapter 10, Improving Performance, discusses Elasticsearch performance improvements under different loads and what the right way of scaling production clusters is, along with covering the insights into garbage collections and hot threads issues and how to deal with them. It further covers query profiling and query benchmarking. In the end, it explains the general Elasticsearch cluster tuning advice under high query rate scenarios versus high indexing throughput scenarios.

Chapter 11, Developing Elasticsearch Plugins, covers Elasticsearch plugins' development by showing and describing in depth how to write your own REST action and language analysis plugin.

Chapter 12, Introducing Elastic Stack 5.0, introduces you to the components of Elastic Stack 5.0, covering Elasticsearch, Logstash, Kibana, and Beats.

What you need for this book

This book was written using Elasticsearch 5.0.x, and all the examples and functions should work with it. In addition to that, you'll need a command-line tool that allows you to send HTTP requests such as curl, which are available for most operating systems. Please note that all examples in this book use the mentioned curl tool. If you want to use another tool, please remember to format the request in an appropriate way that is understood by the tool of your choice.

In addition to that, to run examples in Chapter 11, Developing Elasticsearch Plugins, you will need a Java Development Kit (JDK) Version 1.8.0_73 and above installed and an editor that will allow you to develop your code (or a Java IDE such as Eclipse). To build the code and manage dependencies in Chapter 11, Developing Elasticsearch Plugins, we are using Apache Maven.

The last chapter of this book has been written using Elastic Stack 5.0.0, so you will need to have Logstash, Kibana, and Metricbeat, all comprising the same version.

Who this book is for

This book was written for Elasticsearch users and enthusiasts who are already familiar with the basic concepts of this great search server and want to extend their knowledge of Elasticsearch. It also covers topics such as how Apache Lucene or Elasticsearch works, along with getting aware of the changes from Elasticsearch 1.x to 5.x. In addition to that, readers who want to see how to improve their query relevancy and learn how to extend Elasticsearch with their own plugin may find this book interesting and useful.

If you are new to Elasticsearch and you are not familiar with basic concepts, such as querying and data indexing, you may find it a little difficult to use this book as most of the chapters assume that you have this knowledge already.

Conventions

In this book, you will find a number of styles of text that distinguish between different kinds of information. Here are some examples of these styles, and an explanation of their meaning.

Code words in text are shown as follows: "but not the Elasticsearch term in the document field"

A block of code is set as follows:

public class CustomRestActionPlugin extends Plugin implements ActionPlugin {  
  @Override
     public List<Class<? extends RestHandler>> getRestHandlers() {
           return Collections.singletonList(CustomRestAction.class);
     } 
}

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

curl -XGET 'localhost:9200/clients/_search?pretty' -d '{
 "query" : {
  "prefix" : {
   "name" : {
    "prefix" : "j",
    "rewrite" : "constant_score_boolean"
   }
  }
 }
}'

Any command-line input or output is written as follows:

curl -XPUT 'localhost:9200/mastering_meta/_settings' -d '{
 "index" : {
  "auto_expand_replicas" : "0-all"
 }
}

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "field and hit the Create button"

Note

Warnings or important notes appear in a box like this.

Tip

Tips and tricks appear like this.

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